A novel intrusion detection system based on the 2-dimensional space distribution of average matching degree

Author

Wang, Tuo ; Mabu, Shingo ; Lu, Nannan ; Hirasawa, Kotaro

Author_Institution

Grad. Sch. of Inf., Production & Syst., Waseda Univ., Kitakyushu, Japan

fYear

2011

fDate

13-18 Sept. 2011

Firstpage

2829

Lastpage

2834

Abstract

Because of the increasing reliance on the Internet and its worldwide connectivity, Intrusion Detection System (IDS) has attracted the attention of many researchers to strengthen the Internet security. In the field of IDS, anomaly detection still is not a mature technology yet compared with misuse detection. In this paper, a classification model (called Distance-based Classification Model) is improved, which considers both misuse detection and anomaly detection. The evaluation of the proposed model is carried out over NSL-KDD data sets, which consists of selected records of the complete KDD data sets.

Keywords

Internet; pattern classification; security of data; 2-dimensional space distribution; Internet security; NSL-KDD data sets; anomaly detection; average matching degree; distance-based classification model; intrusion detection system; misuse detection; Association rules; Data models; Economic indicators; Intrusion detection; Manganese; Training; Training data; Distance-based Classification Model; Intrusion Detection System; KSL-KDD data sets; NSL-KDD data sets;

fLanguage

English

Publisher

ieee

Conference_Titel

SICE Annual Conference (SICE), 2011 Proceedings of

Conference_Location

Tokyo

ISSN

pending

Print_ISBN

978-1-4577-0714-8

Type

conf

Filename

6060464